Portfolio management with ESG news sentiment
Keywords:ESG, Stock Market Prediction, Sentiment Analysis, News, Big Data.
In this paper, we introduce a novel news sentiment database and analyze its potential applications in the financial markets via several trading experiments. We analyze the predictability of the news sentiment (both general news and ESG-related news) on the return of European stocks and the potential of applying them as a proper trading strategy over seven years from 2015 to 2023. We find that sentiment indicators such as Tone, and Polarity show significant relationships to the return of the stock price. Those relationships can be exploited, even in the most naive way, to create trading strategies that can be profitable and outperform the market. Furthermore, among the indicators, those extracted from ESG-related news tend to show better performance. This sentiment database is available through a bespoke app at the website https://esg.cafe